| name | ceap-enterprise-context |
| description | Use for CEAP enterprise context aggregation, engineering memory, knowledge graphs, cross-system analysis, integrations, D365 or ERP context, documentation intelligence, and workflow observation. |
CEAP Enterprise Context
Use this skill when the task depends on organizational context across repositories, tickets, documents, communication, logs, or enterprise systems.
Workflow
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Define context boundaries.
- Identify which systems matter: repositories, tickets, PRs, docs, logs, Teams, SharePoint, Confluence, Jira, Azure DevOps, GitHub, ServiceNow, ERP, D365, observability, cloud, or CI/CD.
- Capture privacy, governance, tenant, and retention constraints before using sensitive sources.
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Build a context graph.
- Connect tickets, code, APIs, services, data flows, incidents, deployments, architectural decisions, and historical reviews.
- Reuse existing engineering memory, playbooks, team conventions, and recurring solution patterns.
- Distinguish verified facts from inferred relationships.
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Analyze cross-system impact.
- Look for dependency chains, integration contracts, critical paths, hidden process coupling, recurring failure patterns, and operational risk.
- Correlate tickets, logs, incidents, PRs, and documentation.
- Surface gaps where missing data prevents a confident recommendation.
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Produce reusable memory.
- Summarize durable decisions, patterns, root causes, and playbooks in a form that can be reused.
- Avoid storing secrets, unnecessary personal data, or unapproved sensitive details.
Feature Coverage
- Engineering memory, long-term context, knowledge graphs, semantic search, document analysis, and context compression
- Historical PR and review analysis, team-convention learning, architecture decision history, incident correlation, and reusable playbooks
- GitHub, Azure DevOps, Jira, ServiceNow, Teams, SharePoint, Confluence, D365, ERP, SIEM, CI/CD, MCP, GitLab, Kubernetes, Docker, cloud, observability, SAP, REST, GraphQL, event streaming, OpenTelemetry, LangGraph, and LangChain integrations
- Workflow observation, IDE activity analysis, build and debugging detection, browser-context analysis, OCR-based screen analysis, pattern extraction, process mining, and productivity analysis
Output Shape
Return:
- Context sources used
- Verified facts
- Inferred relationships
- Impact map
- Missing context
- Reusable memory entries